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Voyage Planning

Advanced weather routing and intelligent voyage planning to ensure optimal ETA management and operational efficiency.

Overview

SimBlue Marine's advanced voyage planning platform focuses on acoustic impact assessment and underwater noise optimization for marine operations. Our comprehensive system integrates real-time acoustic modeling, vessel performance analytics, and environmental impact assessment to minimize underwater noise pollution while maintaining operational efficiency. The platform provides detailed acoustic footprint analysis, noise exposure level comparisons, and optimization strategies that enable maritime operators to make environmentally conscious routing decisions while ensuring safe and efficient vessel operations.

Core Capabilities

Real-time acoustic modeling and underwater noise analysis for marine operations, providing detailed assessment of vessel acoustic footprints and environmental impact.
Advanced algorithms that optimize vessel routes to minimize underwater noise pollution while maintaining operational efficiency and safety standards.
Comprehensive environmental assessment tools providing detailed analysis of acoustic impact on marine ecosystems and wildlife.
Comparative analysis between conventional AIS-based operations and optimized acoustic-aware routing strategies.
Dynamic visualization platform for real-time acoustic footprint analysis and sound propagation pattern monitoring in marine environments.

Our Acoustic-Aware Voyage Planning Services Include

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Research Profile

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Latest Publications on Voyage Planning & Marine Operations

"Predicting transmission loss in underwater acoustics using continual learning with range-dependent conditional convolutional neural networks"
I. Kant Deo, A. Venkateshwaran, R. K. Jaiman, Journal of the Acoustical Society of America, 2025
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"A multi-objective optimization framework for reducing the impact of ship noise on marine mammals"
A. Venkateshwaran, I. Kant Deo, J. Jelovica, R. K. Jaiman, Ocean Engineering, 2024
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"Predicting Wave Propagation for Varying Bathymetry Using Conditional Convolutional Autoencoder Network"
I. Kant Deo, A. Venkateshwaran, R. Jaiman, ASME OMAE Conference, 2024
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